Species distribution models (SDMs) have been frequently employed to forecast the response of alpine plants to global changes. Efforts to model alpine plant distribution have thus far been primarily based on a correlative approach, in which ecological processes are implicitly addressed through a statistical relationship between observed species occurrences and environmental predictors. Recent evidence, however, highlights the shortcomings of correlative SDMs, especially in alpine landscapes where plant species tend to be decoupled from atmospheric conditions in micro-topographic habitats and are particularly exposed to geomorphic disturbances. While alpine plants respond to the same limiting factors as plants found at lower elevations, alpine environments impose a particular set of scale-dependent and hierarchical drivers that shape the realized niche of species and that require explicit consideration in a modelling context. Several recent studies in the European Alps have successfully integrated both correlative and process-based elements into distribution models of alpine plants, but for the time being a single integrative modelling framework that includes all key drivers remains elusive. As a first step in working toward a comprehensive integrated model applicable to alpine plant communities, we propose a conceptual framework that structures the primary mechanisms affecting alpine plant distributions. We group processes into four categories, including multi-scalar abiotic drivers, gradient dependent species interactions, dispersal and spatial–temporal plant responses to disturbance. Finally, we propose a methodological framework aimed at developing an integrated model to better predict alpine plant distribution.

中文翻译：

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致力于高山植物分布的综合模型。

物种分布模型 (SDM) 经常被用来预测高山植物对全球变化的响应。迄今为止，对高山植物分布进行建模的努力主要基于相关方法，其中生态过程通过观察到的物种发生与环境预测因子之间的统计关系隐含地解决。然而，最近的证据强调了相关 SDM 的缺点，特别是在高山景观中，植物物种往往与微地形栖息地的大气条件脱钩，并且特别容易受到地貌干扰。虽然高山植物对低海拔植物的限制因素有相同的反应，高山环境强加了一组特定的规模依赖和分层驱动因素，这些驱动因素塑造了已实现的物种生态位，并且需要在建模环境中明确考虑。最近在欧洲阿尔卑斯山进行的几项研究已成功地将相关和基于过程的元素集成到高山植物的分布模型中，但目前一个包含所有关键驱动因素的单一集成建模框架仍然难以捉摸。作为朝着适用于高山植物群落的综合综合模型迈出的第一步，我们提出了一个概念框架，该框架构建了影响高山植物分布的主要机制。我们将过程分为四类，包括多标量非生物驱动因素、梯度依赖性物种相互作用、分散和时空植物对干扰的反应。最后，我们提出了一个方法框架，旨在开发一个综合模型，以更好地预测高山植物分布。